Skip to content
体验新版
项目
组织
正在加载...
登录
切换导航
打开侧边栏
Greenplum
Opencv
提交
ef1690ef
O
Opencv
项目概览
Greenplum
/
Opencv
11 个月 前同步成功
通知
7
Star
0
Fork
0
代码
文件
提交
分支
Tags
贡献者
分支图
Diff
Issue
0
列表
看板
标记
里程碑
合并请求
0
DevOps
流水线
流水线任务
计划
Wiki
0
Wiki
分析
仓库
DevOps
项目成员
Pages
O
Opencv
项目概览
项目概览
详情
发布
仓库
仓库
文件
提交
分支
标签
贡献者
分支图
比较
Issue
0
Issue
0
列表
看板
标记
里程碑
合并请求
0
合并请求
0
Pages
DevOps
DevOps
流水线
流水线任务
计划
分析
分析
仓库分析
DevOps
Wiki
0
Wiki
成员
成员
收起侧边栏
关闭侧边栏
动态
分支图
创建新Issue
流水线任务
提交
Issue看板
体验新版 GitCode,发现更多精彩内容 >>
提交
ef1690ef
编写于
7月 22, 2020
作者:
M
Maksim Shabunin
浏览文件
操作
浏览文件
下载
差异文件
Merge pull request #17913 from asmorkalov:as/connected_components_ref
上级
0fa06b1d
abceef74
变更
2
隐藏空白更改
内联
并排
Showing
2 changed file
with
16 addition
and
3 deletion
+16
-3
doc/opencv.bib
doc/opencv.bib
+13
-0
modules/imgproc/include/opencv2/imgproc.hpp
modules/imgproc/include/opencv2/imgproc.hpp
+3
-3
未找到文件。
doc/opencv.bib
浏览文件 @
ef1690ef
...
...
@@ -1215,3 +1215,16 @@
year
=
{1996}
,
publisher
=
{Elsevier}
}
@Article
{
Wu2009
,
author
=
{Wu, Kesheng
and Otoo, Ekow
and Suzuki, Kenji}
,
title
=
{Optimizing two-pass connected-component labeling algorithms}
,
journal
=
{Pattern Analysis and Applications}
,
year
=
{2009}
,
month
=
{Jun}
,
day
=
{01}
,
volume
=
{12}
,
number
=
{2}
,
pages
=
{117-135}
,
}
modules/imgproc/include/opencv2/imgproc.hpp
浏览文件 @
ef1690ef
...
...
@@ -403,7 +403,7 @@ enum ConnectedComponentsTypes {
//! connected components algorithm
enum
ConnectedComponentsAlgorithmsTypes
{
CCL_WU
=
0
,
//!< SAUF algorithm for 8-way connectivity, SAUF algorithm for 4-way connectivity
CCL_WU
=
0
,
//!< SAUF
@cite Wu2009
algorithm for 8-way connectivity, SAUF algorithm for 4-way connectivity
CCL_DEFAULT
=
-
1
,
//!< BBDT algorithm for 8-way connectivity, SAUF algorithm for 4-way connectivity
CCL_GRANA
=
1
//!< BBDT algorithm for 8-way connectivity, SAUF algorithm for 4-way connectivity
};
...
...
@@ -3842,7 +3842,7 @@ image with 4 or 8 way connectivity - returns N, the total number of labels [0, N
represents the background label. ltype specifies the output label image type, an important
consideration based on the total number of labels or alternatively the total number of pixels in
the source image. ccltype specifies the connected components labeling algorithm to use, currently
Grana (BBDT) and Wu's (SAUF) algorithms are supported, see the #ConnectedComponentsAlgorithmsTypes
Grana (BBDT) and Wu's (SAUF)
@cite Wu2009
algorithms are supported, see the #ConnectedComponentsAlgorithmsTypes
for details. Note that SAUF algorithm forces a row major ordering of labels while BBDT does not.
This function uses parallel version of both Grana and Wu's algorithms if at least one allowed
parallel framework is enabled and if the rows of the image are at least twice the number returned by #getNumberOfCPUs.
...
...
@@ -3874,7 +3874,7 @@ image with 4 or 8 way connectivity - returns N, the total number of labels [0, N
represents the background label. ltype specifies the output label image type, an important
consideration based on the total number of labels or alternatively the total number of pixels in
the source image. ccltype specifies the connected components labeling algorithm to use, currently
Grana's (BBDT) and Wu's (SAUF) algorithms are supported, see the #ConnectedComponentsAlgorithmsTypes
Grana's (BBDT) and Wu's (SAUF)
@cite Wu2009
algorithms are supported, see the #ConnectedComponentsAlgorithmsTypes
for details. Note that SAUF algorithm forces a row major ordering of labels while BBDT does not.
This function uses parallel version of both Grana and Wu's algorithms (statistics included) if at least one allowed
parallel framework is enabled and if the rows of the image are at least twice the number returned by #getNumberOfCPUs.
...
...
编辑
预览
Markdown
is supported
0%
请重试
或
添加新附件
.
添加附件
取消
You are about to add
0
people
to the discussion. Proceed with caution.
先完成此消息的编辑!
取消
想要评论请
注册
或
登录